[Mention The Feature]: Adding Tutorial on how to develop a Email Spam Classifier Using DL in project page website.

[IkkiOcean]

Is your feature request related to a problem? Please describe.

We need to create a comprehensive tutorial that guides users through the process of developing an email spam classifier using deep learning techniques. This tutorial should be suitable for beginners and cover all essential aspects, from data preparation to model evaluation.

Describe the solution you'd like.

Proposed Steps:

1. Introduction:

   • Brief overview of spam classification and its importance.
   • Explanation of deep learning and its advantages in classification tasks.

2. Dataset:

   • Identify and provide access to a suitable dataset for email classification (e.g., Enron Email Dataset, SpamAssassin Public Corpus).
   • Instructions on how to preprocess the dataset (cleaning text, removing stop words, etc.).

3. Model Development:

   • Step-by-step guide on setting up the deep learning environment (e.g., using TensorFlow/Keras or PyTorch).
   • Building the model architecture (e.g., using LSTM, CNN, or Transformer-based models).
   • Explanation of hyperparameters and their importance.

4. Training the Model:

   • Instructions on training the model, including batching, validation, and metrics.
   • Techniques for optimizing model performance (e.g., early stopping, learning rate scheduling).

5. Evaluation:

   • Methods to evaluate the model's performance using metrics like accuracy, precision, recall, and F1 score.
   • Visualizations of the results (e.g., confusion matrix, ROC curve).

6. Deployment:

   • Brief overview of how to deploy the trained model for real-time email classification (e.g., using Flask or FastAPI).

7. Conclusion:

   • Summary of key takeaways and potential improvements for the classifier.
   • Suggestions for further reading or projects related to spam classification.

Describe alternatives you've considered.

No response

Additional context.

No response

Show us the magic with screenshots

No response

Checklist

• [X] I have checked the Existing Issues
• [X] I have read the Contributing Guidelines
• [X] I want to work on this issue. (optional)

[vivekvardhan2810]

@IkkiOcean assigning this issue to you.

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